Provided is a robot, including: a plurality of sensors; a processor; a tangible, non-transitory, machine readable medium storing instructions that when executed by the processor effectuates operations including: capturing, with an image sensor, images of a workspace as the robot moves within the workspace; identifying, with the processor, at least one characteristic of at least one object captured in the images of the workspace; determining, with the processor, an object type of the at least one object based on characteristics of different types of objects stored in an object dictionary, wherein possible object types comprise a type of clothing, a cord, a type of pet bodily waste, and a shoe; and instructing, with the processor, the robot to execute at least one action based on the object type of the at least one object.
Legal claims defining the scope of protection, as filed with the USPTO.
4. The robot of claim 1, wherein the at least one action comprises driving around the at least one object and continuing along a planned navigation path or driving along a modified navigation path.
5. The robot of claim 1, wherein the at least one characteristic comprises any of: an edge, a shape, and a color.
6. The robot of claim 1, wherein the image sensor comprises a field of view, the field of view including at least an area ahead of the robot.
9. The robot of claim 8, wherein the possible object types further comprise at least one of: a type of toy, a type of animals, a type of food, a plastic bag, jewelry, shoelaces, and keys.
11. The robot of claim 1, wherein the processor determines the object type of the at least one object using machine learning techniques.
15. The media of claim 12, wherein the at least one action comprises driving around the at least one object and continuing on a planned navigation path or driving along a modified navigation path.
16. The media of claim 12, wherein the at least one characteristic comprises any of: an edge, a shape, and a color.
19. The media of claim 18, wherein the possible object types further comprise at least one of: a type of toy, a type of animals, a type of food, a plastic bag, jewelry, shoelaces, and keys.
20. The media of claim 12, wherein the image sensor comprises a field of view, the field of view including at least an area ahead of the robot.
22. The media of claim 12, wherein the processor determines the object type of the at least one object using machine learning techniques.
26. The method of claim 23, wherein the at least one action comprises driving around the at least one object and continuing along a planned navigation path or driving along a modified navigation path.
27. The method of claim 23, wherein the at least one characteristic comprises any of: an edge, a shape, and a color.
28. The method of claim 23, wherein the image sensor comprises a field of view, the field of view including at least an area ahead of the robot.
31. The method of claim 23, wherein the processor determines the object type of the at least one object using machine learning techniques.
33. The method of claim 32, wherein the possible object types further comprise at least one of: a type of toy, a type of animals, a type of food, a plastic bag, jewelry, shoelaces, and keys.
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May 22, 2023
April 23, 2024
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